Fugitive gas detection system

ABSTRACT

A fugitive gas detection system is provided. The system includes a cloud service, a plurality of reach-based components, a plurality of wireless gas sensors. The reach-based components comprise backhauls and gateways. The wireless gas sensors are acted as nodes to acquire sensor data in a local mesh network and the nodes are connected to the cloud service through the reach-based components, one node can transmit the sensor data to other sensor nodes of the local mesh network. The system measures flammable gas levels with speed, economy and accuracy.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 62/611,391, filed Dec. 28, 2017; U.S. ProvisionalApplication No. 62/617,855, filed Jan. 16, 2018, U.S. Provisional No.62/617,899, filed Jan. 16, 2018; U.S. Provisional No. 62/662,977, filedJan. 16, 2018; U.S. application Ser. No. 15/980,445, filed May 15, 2018;and PCT Application No. PCT/US2018/032725, filed May 15, 2018, thedisclosures of which are incorporated herein by reference in itsentirety.

FIELD

The disclosure relates generally to analysis instruments and sensors.The disclosure relates specifically to gas sensors for detecting gasleaks in the oil and gas industry.

BACKGROUND

Fire and explosion are some of the most serious hazards associated withhydrocarbon production. During drilling, fracturing, completions andother oil well exploration and production processes, there are ampleopportunities for hydrocarbon gas or vapor to be released. Detectingboth systematic and random leaks in the oil and gas industry has becomea priority for operators upstream, midstream, and downstream. Due to theexplosive nature of gas, it is necessary to locate and repair leaks toprevent accidents and to keep operations at their optimum. Preventingaccidents not only saves lives and assets, but also minimizes productionlosses. Additionally, the emissions of these toxins have been found tobe damaging to the environment, for example, USA, Canada and Mexicoaccount for nearly 20% of global oil and gas methane pollution.Available athttps://www.edf.org/sites/default/files/na-methane-policy-brief_english.pdf.Governmental agencies around the world now require operators to monitorand remediate leaks in their processes.

Gas leaks are present in all phases of currently operational oil and gasprocesses and at abandoned and orphaned oil wells. Leaks are identifiedat pressure points in the systems, such as at plugs, seals, gaskets andvalves. From pipelines through refineries to storage facilities, leakscan be detected and mitigated through a variety of technological.Majority of oil and gas fugitive and vented emissions are methane (CH₄)emissions that come from: Natural gas production, processing,transmission, distribution and oil production. While fugitive gas isprimarily methane, it also contains other heavier hydrocarbons such asethane, propane, butane and acetone.

Fugitive gas on any oil and gas production site is a hazard not only tothe hydrocarbon emissions of the collective Greenhouse Gases (GHG), butalso poses immediate risk for explosions when it comes in contact withdiesel engines.

Governments are imposing legislation on the oil and gas industry toremedy methane emissions. This is driving technological advances in gasdetection in a number of ways. Firstly, detecting hazardous levels ofcombustible gas or solvent vapor in air, which is expressed in % LowerExplosive Limit (LEL) has become a requirement in hazardous areas suchas oil fields that have active machinery. Secondly, a drastic reductionin the footprint of sensors units make them easy to distribute acrossthe facility for triangulation of fugitive sources. Additionally,utilizing MEMS-based programming, connectivity and intelligence is moreeasily adapted to the sensor unit such as: diagnostics, analytics,communication protocols and mitigation procedures. The instrumentationwill be exposed to harsh conditions and foul weather; therefore, it mustbe ruggedized and affordably replaced often.

While the most common solution is still “visual inspection/detection bya person walking (or driving or flying over)”, there are a number of newtechnologies that have been developed to answer the call of this growingissue. To-date, Acoustic/Ultrasonic, Infrared, Fiber Optic, HydrocarbonSensing Cables, Mass Volume, Negative Pressure Wave, StatisticalAnalysis, RTTM and E-RTTM have all been deployed in the industry. Theneed to understand behavior of the fugitive gases has accelerated thedevelopment of new technologies that can provide constant monitoring andthe capture of relevant historical data.

The foregoing has outlined rather broadly the features of the presentdisclosure in order that the detailed description that follows may bebetter understood. Additional features and advantages of the disclosurewill be described hereinafter, which form the subject of the claims.

SUMMARY

An embodiment of the fugitive gas detection system comprises a cloudservice; a plurality of reach-based components; a plurality of wirelessgas sensors operating as nodes to acquire sensor data; wherein the nodesare connected to the cloud service through the reach-based components.In an embodiment, the reach-based components comprise backhauls andgateways. In an embodiment, the nodes are deployed near a monitoringfield to form a local mesh network through self-organization, nodes cantransmit the sensor data to other sensor nodes of the local meshnetwork. In an embodiment, the gas sensor is a MEMS based multigassensor. In an embodiment, the MEMS based multigas sensor includes aplurality of probes to detect special qualities of a gas. In anembodiment, the special qualities of the measured gas are recorded by aradar chart, the MEMS based multigas sensor detects the species andconcentration of the gas using the radar chart. In an embodiment, thegas is selected from the group consisting of methane, ethane, propane,butane, acetone, and methanol. In an embodiment, the gas a mixture ofany two or more species of methane, ethane, propane, butane and acetone.In an embodiment, comprising each of the nodes includes an autonomouslocal controller. In an embodiment, the nodes further comprising sensorsselected from level sensors, vibration sensors, state of valve sensorsand pressure transducers. In an embodiment, the system further comprisesan on-board GPS on each node. In an embodiment, the system furthercomprises an Industrial Internet of Things (IIoT) platform. In anembodiment, the system operates risk analysis using the sensors todetermine a probability of risk for a given industrial site. In anembodiment, the system runs in a local controller mode in which eachnode is stand-alone and runs singularly and autonomously. In anembodiment, the system runs in a few nodes controller mode in which apotentially small number of nodes are operating autonomously and in amesh network. In an embodiment, the system runs in a local mesh withlocal gateway mode in which local collection sensors and/or controllersare monitored by a local gateway. In an embodiment, the system runs inan autonomous mode in which local decision-making is included in theIIoT platform. In an embodiment, the system runs in a data analyticsmode in which cloud-based data is analyzed by taking current andhistorical data to evaluate systemic releases, calculate long term riskperformance and behavior. In an embodiment, the system runs edgecomputing algorithms allowing for local decisions to be made at thesensors. In an embodiment, the local decisions are selected from thegroup consisting of valve closure upon gas detection, valve closureafter receiving kill signal from other nodes.

The present disclosure is directed to systems that may detect speciesand concentration of an explosive or flammable gas for a givenindustrial site. The gas can be methane, ethane, propane, butane,acetone, and methanol or a mixture of above compound. In oneillustrative embodiment of a system in accordance with the presentdisclosure, the system includes a cloud service, a plurality ofreach-based components, a plurality of wireless gas sensors. thereach-based components comprise backhauls and gateways. The wireless gassensors are acted as nodes to acquire sensor data in a local meshnetwork and the nodes are connected to the cloud service through thereach-based components, one node can transmit the sensor data to othersensor nodes of the local mesh network. The gas sensor may be a MEMSbased multigas sensor including a plurality of probes to detect specialqualities of the gas. The special qualities of the measured gas arerecorded by a radar chart, the MEMS based multigas sensor detects thespecies and concentration of the gas using the radar chart.

In some embodiments, each of the nodes includes an autonomous localcontroller and an on-board GPS.

The system further comprising an Industrial Internet of Things (IIoT)platform and can run in the following modes: local controller mode inwhich each node is stand-alone and runs singularly and autonomously; fewnodes controller mode in which a potentially small number of nodes areoperating autonomously and in a mesh network; local mesh with localgateway mode in which local collection sensors and/or controllers aremonitored by a local gateway; autonomous mode in which localdecision-making is included in the IIoT platform. A data analytics modein which cloud-based data is analyzed by taking current and historicaldata to evaluate systemic releases, calculate long term risk performanceand behavior. the system can run edge computing algorithms allowing forlocal decisions to be made at the sensors. The local decisions areselected from the group consisting of valve closure upon gas detection,valve closure after receiving kill signal from other nodes. The systemcan operate risk analysis using the sensors to determine a probabilityof risk for a given industrial site.

In some embodiments, the nodes further comprise sensors such as levelsensors, vibration sensors, state of valve sensors and pressuretransducers.

The system measures flammable gas levels with speed, economy andaccuracy. Advanced sensor technology and sophisticated analysis softwareallows for the rapid detection, identification and quantification of awide variety of gases. This sensor is able to identify and quantifymultiple flammable gases on a single chip complete with accurate LELdetermination. The system provides geolocation, and long-range wirelessconnectivity. Sensors can be deployed on fixed, mobile, and ancillaryassets. Broad-based deployment becomes feasible by dramatically loweringthe footprint utilizing a silicon lab-on-a-chip sensor. With its siliconcost-structure, large scale sensor deployment becomes feasible.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the manner in which the above-recited and otherenhancements and objects of the disclosure are obtained, a moreparticular description of the disclosure briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the disclosure and are therefore notto be considered limiting of its scope, the disclosure will be describedwith additional specificity and detail through the use of theaccompanying drawings in which:

FIG. 1 is a radar chart showing a measured result of a sensor inaccordance with one aspect of the present disclosure;

FIG. 2 depicts a graphic illustrating an arrangement of several sensorsbased at multiple locations in a given site with communication to alocal central controller in accordance with the present disclosure.

FIG. 3 depicts a schematic arrangement of one illustrative embodiment ofa cloud-based system and wireless sensor networks in accordance with thepresent disclosure;

FIG. 4 shows a sample mesh networks including gateway connecting to acloud;

FIG. 5A-5B depict a table and graph showing the parameters of sensors ofthe system;

FIG. 6 depicts a graphic illustrating the parameters of sensors andcontrollers of the system;

FIG. 7 depicts architecture of a commercial product TTH (the thingsnetwork); and

FIG. 8 depicts architecture of TICK stack, a commercial product.

DETAILED DESCRIPTION

The particulars shown herein are by way of example and for purposes ofillustrative discussion of the preferred embodiments of the presentdisclosure only and are presented in the cause of providing what isbelieved to be the most useful and readily understood description of theprinciples and conceptual aspects of various embodiments of thedisclosure. In this regard, no attempt is made to show structuraldetails of the disclosure in more detail than is necessary for thefundamental understanding of the disclosure, the description taken withthe drawings making apparent to those skilled in the art how the severalforms of the disclosure may be embodied in practice.

The following definitions and explanations are meant and intended to becontrolling in any future construction unless clearly and unambiguouslymodified in the following examples or when application of the meaningrenders any construction meaningless or essentially meaningless. Incases where the construction of the term would render it meaningless oressentially meaningless, the definition should be taken from Webster'sDictionary 3rd Edition.

Conventionally, various types of combustible gas sensors are utilizedthroughout the oil and gas industry in the largely manual detection ofsingular gases. Technologies utilized include electrochemical,photoionization, metal oxide semiconductor, catalytic, infrared, andlaser. But these sensors only detect a single species. Therefore, inorder to detect different combustible gases such as methane, ethane,propane, butane and acetone, different kinds of gas sensors should beemployed to detect different kinds of gas, which will Increase the costand complicate the gas detection system. Additionally, conventional gassensors do not detect others or significantly under-report other gases.

In some embodiments, a MEMS based multigas sensor using a variety ofon-chip tests to determine which gas is being detected is illustrated.Multiple probes of the multigas sensor are included in a MEMS arrayconstructed using semiconductor fabrication techniques. Each probedetects a special quality of the measured gas. All the measured resultson the probes can determine which gas is detected. Special qualities ofthe measured gas include but not limited to redox potential, airviscosity, air pH and many other analyses such as differential thermalanalysis (DTA) and differential scanning calorimetry (DSC). Differentgases have different sensitivity on different probes of the MEMS basedmultigas sensor, just like different materials having differentcharacteristic spectrum in spectral analysis. In one embodiment, theMEMS based multigas sensor has 48 probes to detect 48 special qualitiesof the measured gas. Referring to FIG. 1, a radar chart shows themeasured result of the sensor. Each test or value is a different spokeon the radar chart to represent a special quality of the measured gas.Different kinds of gases have different values on different spokes. Eventwo same kind of gases will have different values on the same spoke ifthey have different concentration. The radar charts of different gaseswith different concentration can be stored in a memory prior toperforming detection. During the process of detection, data collectedfrom the probes of the MEMS based multigas sensor forms an instant radarchart. Comparing the instant radar chart and radar charts stored in thememory, the matched chart in the memory indicates the gas type and itsconcentration.

In some embodiments, the fugitive gas is a mixture of compoundscomprising such as methane and ethane or further comprising propane.Prior to performing detection, the response of the probes of the sensorcorresponding to the mixture with different concentrations can be storedin a memory to form a table. In an embodiment, each concentration of themixture corresponds values of the probes. Then the sensor detects themixture and gets detection values of the probes, a program is employedto looking up in the table the response characteristics and matchingagainst an existing response. In some embodiments, the Multigas sensoris a detector made by Nevada Nanotech Inc.

In some embodiments, the sensor can detect new gas. Historically toteach a detector a new gas takes much time and money to quantify each ofthe detected parameters and to correlate an effect from a compound withan individual test. This is a reductionist-based method and certainly isthe most complete, and versatile. However, simply exposing the detectorto a compound and recording electronically the response can perform aqualitative method of calibrating to a new gas. To be sure, there is noknowledge of any chemical quality of the new compound, except for thedetector response. For example, Prior to performing detection, theresponse of the probes of the sensor corresponding to the new compoundwith different concentrations can be stored in a memory to form a table.Exposing the sensor to the compound and recording electronically theresponse, looking up in the table the response characteristics andmatching against an existing response, such that the concentration ofthe new compound can be determined. The key point is the gas does noteven have to be known to learn. This allows the calibration andeducation for a new gas species to occur in seconds rather than months.

A plurality of the sensors can be used in a fugitive gas detectionsystem to monitor and quantify gas emissions at oil and gas explorationand production sites, refineries, storage and transmission facilities.Through this system, gas emissions can be monitored, mapped and analyzedin real-time, providing the intelligence necessary for immediateremediation of methane and other combustible emission sources.

FIG. 2 graphically depicts one arrangement of several sensors based atmultiple locations in a given site with communication to a local centralcontroller in accordance with the present disclosure. Sensors aredeployed throughout a hydrocarbon production or processing site. Thesemay be sensor 1 on or near production sites and storage, sensor 2 on ornear engines servicing the hydrocarbon production site and sensors 3 and5 on or near engines on vehicles. A local central controller 4 may alsobe disposed at the site. The sensors and local central controller 4 maybe in operative communication via a wireless network or wired networksor as is otherwise known in the art. The local controller 4 may be incommunication with a cloud based backup or remote controller.

FIG. 3 depicts a schematic arrangement of one illustrative embodiment ofa cloud-based system and wireless sensor networks in accordance with thepresent disclosure. The system includes a cloud service, a gateway and aplurality of wireless sensors. For simplicity, only one wireless sensoris shown in FIG. 3, however, the system may include a plurality ofwireless sensors located across a wide area. The wireless sensoroperates as a node to acquire sensor data. The wireless sensor has theability to connect to a gateway or other wireless sensors. Theillustrative wireless sensor includes a gas sensor box. A processor, adisplayer, a serial of I/O and debug interface, a gas sensor, an SSR(Scalable Source Routing) module and a wireless communication module areall assembled in the box. The processor controls the gas sensor todetect gas where the wireless sensor deployed. When the concentrationand type of the gas is determined, the processor drives the displayer todisplay the detection results. SSR is a routing protocol for the sensornetwork. Every node periodically broadcasts a “hello” message to itsphysical neighbor sensors, notifying the neighbor sensors of itsexistence. “Hello” messages include a list of the physical neighborsensors of each node. If the node finds itself included in the “hello”message of another node, it assumes a bidirectional connection, and addsthe other node to its list of physical peers. The I/O and debuginterface allows simplifying development and debugging the wirelesssensor. In one embodiment, a plurality of sensor nodes deploys near themonitoring field to form a local mesh network through self-organization,Sensor nodes monitor the collected data to transmit along to othersensor nodes. The short-range communication networks can be but notlimit to a Bluetooth type of network, a ZigBee type of network or a WiFitype of network.

In some embodiments, the node can further include autonomous, low-costsensor/controllers in wireless communication and subscribed to the localmesh. One node can cause action to other node in the local mesh network.For instance, a first sensor in a first node detects a high andincreasing level of methane, it will transfer the message to the cloudservice and operate some local action before receiving control signalfrom the cloud service. Local action includes first shutting off theassociated engine electronically. If conventional means do not shut-offthe engine, an air intake shutoff valve is actuated, stopping all intakeair from entering the engine. Immediately thereafter, the autonomoussensor sends an alert to other nearest-neighbor members of the mesh toclose their associated valves and stop their engines in anticipation ofthe methane concentration increase.

In some embodiments, each controller contains a wide variety of hardwarecomponents. The system includes an on-board GPS on each mesh node. Agateway controller monitors continuously the location of each node inreal time. This allows local action or control of specific member nodesbased on physical location (such as downwind from a gas release) orphysical proximity (such as nearest neighbors to a release site or othermesh members). The nodes each self-report their location and proximityto each other, even after movement within the field, providing completeease of use and no need of reassignment by an administrator.

Traditional hub and spoke networks relied entirely upon the device inthe middle that served no other purpose but to regulate traffic toanother hub upstream. Mesh networks rely on peer-to-peer communicationand allow each node to decide which hub in its range it may select atany given moment based on signal strength and network traffic. This alsonegates network failure due to a single hub collapse. It is trulyself-healing in that each of the nodes contain the intelligence to findthe most efficient pathway for the data they carry.

The wireless sensor nodes are connected to the cloud service through agateway. FIG. 4 shows a sample mesh networks including gatewayconnecting to a cloud. A plurality of sensor nodes 20 are connected to arouter 25 and a plurality of router 25 are connected to a gateway 30 byshort-range wireless connectivity. The gateway 30 is connected to thecloud service 40 using long-range wireless connectivity. the cloudservice 40 can collect data from all of the sensor nodes 20 and outputcontrol signals to different kinds of actuators in the system to preventfire and explosion near the monitoring field.

The gateway 30 is responsible for mesh element membersubscription/de-subscription. This includes mobile assets that containwireless sensors. A truck that has a wireless sensor joins the mesh whenwithin a critical radius, such as a drilling lease. As the mobile assetleaves the location, it is de-subscribed from the mesh.

-   -   Mesh with gateway and cloud reporting: Each installation is        easily configured to log location, gas species and        concentration. This has specific value for forensic discovery in        the event of an explosive gas release, site explosion, or other        similar event.    -   Mesh network with gateway and proprietary backhaul to enable        communication to and from the cloud, even in areas with no        conventional wireless service. The system uses long range        repeaters that allow prompt cloud IO based on multiple long        range wireless protocols including LoRaWAN, Zigbee and others.

In an embodiment, the system is comprised of the followingsub-components:

-   -   Mesh network element: Autonomous, low-cost sensor/controllers in        wireless communication and subscribed to the local mesh. One        member can cause action to other member in the local mesh        network. For instance, a first sensor detects a high and        increasing level of methane. Local action includes first        shutting off the associated engine electronically. If        conventional means do not shut-off the engine, an air intake        shutoff valve is actuated, stopping all intake air from entering        the engine. Immediately thereafter, the autonomous sensor sends        an alert to other nearest-neighbor members of the mesh to close        their associated valves and stop their engines in anticipation        of the methane concentration increase.    -   Gateway (executive mesh network controller): The system can be        run with a node subscribe/de-subscribe in place, such that the        members at any moment are the nodes that are truly local.        Specifically, it is important to verify that all members are        local so that if an event, such as a recorded gas release occurs        on a member node, the node is actually in the local area. For        example, if a mobile asset leaves the local environment but does        not de-subscribe, tens of miles down the road, a gas release is        recorded—it does not make sense to cause action at the original        site since the release did not originate there.    -   Backhaul (connection to the cloud): The system can utilize a        chain of very low cost, low-power repeaters to deliver a signal        in a near-instantaneous fashion to a conventional network if        needed. Where wireless is already available, systems can        integrate into commonly deployed networks.

In an embodiment, platform provides user-configurable response andreal-time intelligent insights throughout the local network of fixed,ancillary and mobile assets. Local alerts provide prompt actions andcurrent data to local field personnel.

The fugitive gas detection system can be run with a nodesubscribe/de-subscribe in place, such that the nodes at any moment arethe nodes that are truly local. Specifically, it is important to verifythat all nodes are local so that if an event, such as a recorded gasrelease occurs on a node, the node is actually in the local area. Forexample, if a mobile asset leaves the local environment but does notde-subscribe, tens of miles down the road, a gas release is recorded—itdoes not make sense to cause action at the original site since therelease did not originate there. The system can utilize a chain of verylow cost, low-power repeaters to deliver a signal in anear-instantaneous fashion to a conventional network if needed. Wherewireless is already available, the system can integrate into commonlydeployed networks.

In some embodiments, each wireless sensor is configured to log location,gas species and concentration. This has specific value for forensicdiscovery in the event of an explosive gas release, site explosion, orother similar event, all the data can report to the cloud service 40through the mesh network. Mesh network with gateway and proprietarybackhaul enable communication to and from the cloud service, even inareas with no conventional wireless service. The system uses long rangerepeaters that allow prompt cloud IO based on multiple long-rangewireless protocols including LoRaWAN, Zigbee and others. The system canutilize a chain of very low cost, low-power repeaters to deliver asignal in a near-instantaneous fashion to a conventional network ifneeded. Where wireless is already available, and the system canintegrate into commonly deployed networks.

The system can operate risk analysis using a variety of sensors. Ingeneral, the analysis is straightforward to determine a probability ofrisk for a given industrial site. Each site or node or zone or pipe orconnector or any item has a probability of event, where an event mightbe a leak, a failure to close, or to open, or explosion. A probabilisticmodel where each individual probability of failure over a time intervalis multiplied and the resulting product is the overall probability offailure or risk in the time interval. Conventionally, this has been donewith very long-time intervals, such as a year. However, using very lowcost, wireless sensors to detect leaks such as gas or liquid, or statesof valves, liquid levels or other situations in real time, an instantprobability of risk can be calculated in real time using a mesh network,connected devices and real time calculations. In addition, the data canbe pushed to the cloud service to a time series database for real-timehigher-level analysis.

In some embodiments, the cloud-based system includes an IndustrialInternet of Things (IIoT) platform. The IIoT is a software stack thatcan be embedded into hardware devices such as industrial control systemsor network gateways. The software stack may include its own softwaredevelopment kit (SDK). The SDK includes functions that enable developersto leverage the core features that will described below. A multitude ofsensors and controllers are connected to the IIoT platform by the meshnetwork. The resulting systems, and even the individual sensors andcontrollers, can monitor, collect, exchange, analyze, and instantly acton information to intelligently change their behavior or theirenvironment—all without human intervention.

The cloud-based fugitive gas detection system includes a full IIoTplatform for the purpose of environment monitoring and assetpreservation, chiefly through the real-time monitoring of explosive andcombustible gases including methane, natural gas (with constituentsincluding methane, butane and pentane), explosive and volatile compoundsincluding acetone. Early and prompt gas detection allows rapid anddecisive action to be taken in order to prevent asset destruction andloss of life.

The fugitive gas detection system includes local nodes, wireless andreach-based components. The local nodes comprise sensor, autonomouscontroller, and engine overspeed protection through immediate intake airshut-off. The wireless comprises GPS based location, a true mesh networkof all sensors and controllers. The reach-based components comprisebackhaul and gateway.

The fugitive gas detection system can run in one of the following modes:Local controller mode in which each node is a stand-alone system thatruns singularly and autonomously. Uses include monitoring gas levels andemergency overspeed control of an engine, either using an electronickill signal or by a fully integrated shut-off valve; Few Nodescontroller mode in which a potentially small number of nodes areoperating autonomously and in a true mesh network. Uses include gasmonitoring and engine shutdown of nearest neighbors, once an explosiveor combustible is detected at one controller node; Local mesh with localgateway mode in which a local collection sensors/controllers aremonitored by a local gateway; autonomous mode in which advanced localdecision-making is included in the IIoT package, This will enable amongother tasks, to calculate real time risk; Data Analytics mode in whichcloud-based data is analyzed by taking current and historical data toevaluate systemic releases, calculate long term risk performance andbehavior.

In some embodiments, the fugitive gas detection system uses autonomousmesh network, gateway and backhaul communicate using LoRaWAN™, ZigBee®and other protocols. In addition, each node, the gateway and backhauluse an encrypted and safeguarded protocol that makes any form ofmalicious hacking virtually impossible. Edge computing algorithms allowfor decisions to be made at the sensor level, providing discretedecisions thereby, remediating potential catastrophe. Big data becomesintelligence for historical reference and instant forensic discovery.

In some embodiments, each node includes an autonomous local controllerthat runs a short Linux® stack allowing for rapid action without asignificant software overhead. Local decision making includes valveclosure upon gas detection, valve closure after receiving kill signalfrom other mesh member and other tasks, such as recording non-criticalgas species and concentrations. Beyond that, nodes can perform moremundane tasks such as recording levels of storage tank batteries andrecording flow rates in midstream pipelines.

The fugitive gas detection system includes real-time dashboards todisplay the detection results of the system. The dashboards includelocal display, browser display and micro-display. The local display canbe assigned to selected mesh member nodes, such as those resident intruck cabs or wearable nodes come with a high-resolution color displaythat can display a variety of information including: instantaneous gaslevel concentration and species, temperature, relative humidity andother weather specifics; occurrence of overspeed shut-off valve closure;mesh topology/location of other nearest neighbor mesh members includingtheir status; atmospheric maps provide easily viewable reports of thefield and the current or past status of gas leak events.

The fugitive gas detection system can use cloud communication to setactivation points and display the real time performance of each meshnode. For instance, explosive or volatile gas set points can beimplemented using the cloud interface. Trigger points for different gasclasses can be set. A more sensitive set point for methane than forother gases is common. Cloud based communication provides the real-timereporting of sensor levels, actions taken such as overspeed shutoffvalve actuation, and calculated site risk. The can provide a real-timerisk assessment, in the form of probability. This in turn can be usedto, with the right insurer, change or reduce insurance premiums if thereduction of risk is routinely demonstrated. All cloud-based IO isviewable on any conventional browser from a desktop, laptop, tablet orphone. Any authorized user can see the totality of cloud information asindicated above.

Micro-display is a kind of small robust wireless displays which can bepaired via Bluetooth with every gas detection system including meshnodes, gateway and backhaul. These displays can be set via cloud-basedinstruction to display a variety of information and device statesincluding gas detector response such as gas species, quantity andpercentage of LEL, listing of other mesh members, map location and alarge number of other relevant quantities. The data can be displayed asa table as shown in FIG. 5A or a graph as shown in FIG. 6.

In an embodiment, technology is a platform of wireless nodes, with anarray of digital and analog inputs and outputs. Any detector input isincluded and any response is included.

Detectors can be but not limited to level sensors, vibration sensors,state of valve sensors, pressure transducers, or even simply a change instate or a command from either the cloud based time series database orfrom local node computation.

Outputs can include sending a signal to close a valve, send a message orwork ticket that a tank battery needs to be tended to, or a SMS textnotification to clear an area because it is unsafe. In addition,cloud-based display can be monitored from any browser and automaticactions can be set remotely, say a trigger of action when a liquid levelreaches a certain height.

In an embodiment, the IoT platform can direct action to any type tocause an effect from either the node directly (using its onboardprocessing), or having sent data to the gateway and then to the cloudwhere time series database calculates or processes the incoming data,and arriving at an action, sends an instruction to a specific node, or aseparate device that is devised to cause action, such as opening orclosing a valve, draining a tank or the like. The point is, closing anoverspeed shutoff device is not the only action.

In addition to gas sensor, the fugitive gas detection system can alsoinclude any other sensors. The sensors can be but not limited to levelsensors, vibration sensors, state of valve sensors, pressuretransducers. One specific sensor can be a three axis accelerometerinputting data to a wireless node. The three-axis device actually canreport a three-dimensional vibration shape that corresponds to theengine, motor or other dynamic physical system. Over time, the engine,motor or other will undergo degradation from normal wear and tear orother type of degradation. The three-dimensional representation of thevibration characteristics will change and within certain limits, willreport a new vibration state corresponding to engine deterioration oreven additional engine load, change in fuel, air filter clog or other.Further, over time, the new shapes of three axis vibration potentiallycorrelated with acoustic signals as well can be correlated to actualphysical problems, again such as worn piston rings, poor fuel, excessengine loading, clogged air filter, clogged fuel filter, lack of oil,lack of coolant. In addition, the wireless node can also be attached tothe engine computer port to correlate computer events with vibration andacoustic signals. Also, the device can either warn wirelessly, locallyor over the cloud if the engine needs to be turned off to preventfurther damage.

Various computation techniques can be employed to evaluate the datacollected from the sensors including FFT (fast Fourier transform) of thedata, either locally on the node, or on the cloud. Outputs from thecloud service or the local controller can include sending a signal toclose a valve, send a message or work ticket that a tank battery needsto be tended to, or a SMS text notification to clear an area because itis unsafe. In addition, cloud-based display can be monitored from anybrowser and automatic actions can be set remotely, for example, atrigger of action when a liquid level reaches a certain height.

The fugitive gas detection system allows for a large number ofdeployments including but not limited to overspeed protection, tankfarm/battery monitoring, gas leak detection, tank battery notification,fixed asset tagging and mobile asset tagging.

Overspeed protection in which the gas sensor is used, the system uses anengine overspeed valve (such as is manufactured by PacBrake, PowerHaltand AMOT for three examples). Upon gas detection, and suitable thresholdreached, the system attempts to stop the engine via conventional means.If this does not cause the immediate engine cessation, the valve in theair shutoff closes shutting off the engine by smothering it. In eithercase, a subsequent explosion probability is reduced.

The system can deploy in a tank battery to monitor liquid levels, and todispatch collection when liquid levels match or exceed pre-set levels.

The system can be used for Personal and Personnel Safety. For example,in Canada, it is common to drill or maintain wells with methanol in thewell to suppress condensate. This is during all phases of the well.Every place where there may be a person is a hut due to extreme weather.A small water leak (from produced water) dripping a tiny bit on thefloor can be a huge problem due to the methanol evaporating and making acloud or vapor. A sudden door opening can cause a flash fire. Henceevery worker has to carry two methanol detectors. Two because if a largeamount of methanol gets on the detector surface, it is ruined. Theycannot easily recover from a large methanol burst that damages thedetector, thus the worker would switch to a second detector. The gassensor of the present disclosure is fine if it gets a huge amount ofmethanol. Drench it and it will recover.

The small size of the node allows for a device that is wearable. Theon-board microprocessor can monitor gas sensor from any manufacturerincluding Nevada nanotech for one example. The device also includesstandard long-range wireless radios. In addition, it can includeaccelerometers, heart rate monitors, blood oxygen sensors and the like.Using a long-range compatible gateway, we tri-laterization can be usedto provide a 3-d spatial location of an individual wearing a monitor. Ifthe person falls the accelerometer detects it. The heart rate and bloodO₂ provides additional data. The gas sensor detects and alerts both thewearer and by means of wireless, others outside of the environment ofpotential environmental threats.

The fugitive gas detection system can be deployed around the productionsite with a plurality of gas sensor nodes. Each hut and station can haveone of the networked nodes monitoring for methanol. And Each personnelcan wear a node that has location, gas sensor, basic biometrics (pulse,respiration, falling detector (accelerometer), pulse oximeter) tomeasure workers health and location. If a gas sensor finds methanol, orbasic biometrics detect abnormal physiological indicator, they useLoRaWAN to communicate to other nodes, and to the cloud aboutconcentration and location.

In an embodiment, the system can be utilized for including but notlimited to:

Overspeed Protection—using the sensor technology, the IIoT system and inconjunction with an engine overspeed valve. Upon gas detection, andsuitable threshold reached, the device attempts to stop the engine viaconventional means. If this does not cause the immediate enginecessation, the valve in the air shutoff closes shutting off the engineby smothering it. In either case, a subsequent explosion probability isreduced.

Tank Farm/Battery Monitoring—the system can deploy in a tank battery tomonitor liquid levels, and to dispatch collection when liquid levelsmatch or exceed pre-set levels.

Asset location—semi-fixed assets can be tracked on the yard or in thefield using the systems triangular location. This enables quick and easylocation of similar assets instantly. Mobile assets can easily betracked using our embedded GPS module.

All of the compositions and methods disclosed and claimed herein can bemade and executed without undue experimentation in light of the presentdisclosure. While the compositions and methods of this disclosure havebeen described in terms of preferred embodiments, it will be apparent tothose of skill in the art that variations may be applied to thecompositions and methods and in the steps or in the sequence of steps ofthe methods described herein without departing from the concept, spiritand scope of the disclosure. All such similar substitutes andmodifications apparent to those skilled in the art are deemed to bewithin the spirit, scope and concept of the disclosure as defined by theappended claims.

What is claimed is:
 1. A fugitive gas detection system, comprising, acloud service; a plurality of reach-based components; a plurality ofwireless gas sensors operating as nodes to acquire sensor data; whereinthe nodes are connected to the cloud service through the reach-basedcomponents.
 2. The system of claim 1, wherein the reach-based componentscomprise backhaul s and gateways.
 3. The system of claim 1, wherein thenodes are deployed near a monitoring field to form a local mesh networkthrough self-organization, nodes can transmit the sensor data to othersensor nodes of the local mesh network.
 4. The system of claim 1,wherein the gas sensor is a MEMS based multigas sensor.
 5. The system ofclaim 4, wherein the MEMS based multigas sensor includes a plurality ofprobes to detect special qualities of a gas.
 6. The system of claim 5,wherein the special qualities of the measured gas are recorded by aradar chart, the MEMS based multigas sensor detects the species andconcentration of the gas using the radar chart.
 7. The system of claim4, wherein the gas is selected from the group consisting of methane,ethane, propane, butane, acetone, and methanol.
 8. The system of claim4, wherein the gas a mixture of any two or more species of methane,ethane, propane, butane and acetone.
 9. The system of claim 3, whereincomprising each of the nodes includes an autonomous local controller.10. The system of claim 1, wherein the nodes further comprising sensorsselected from level sensors, vibration sensors, state of valve sensorsand pressure transducers.
 11. The system of claim 1, further comprisingan on-board GPS on each node.
 12. The system of claim 1, furthercomprising an Industrial Internet of Things (IIoT) platform.
 13. Thesystem of claim 12, wherein the system operates risk analysis using thesensors to determine a probability of risk for a given industrial site.14. The system of claim 12, wherein the system runs in a localcontroller mode in which each node is stand-alone and runs singularlyand autonomously.
 15. The system of claim 12, wherein the system runs ina few nodes controller mode in which a potentially small number of nodesare operating autonomously and in a mesh network.
 16. The system ofclaim 12, wherein the system runs in a local mesh with local gatewaymode in which local collection sensors and/or controllers are monitoredby a local gateway.
 17. The system of claim 12, wherein the system runsin an autonomous mode in which local decision-making is included in theIIoT platform.
 18. The system of claim 12, wherein the system runs in adata analytics mode in which cloud-based data is analyzed by takingcurrent and historical data to evaluate systemic releases, calculatelong term risk performance and behavior.
 19. The system of claim 12,wherein the system runs edge computing algorithms allowing for localdecisions to be made at the sensors.
 20. The system of claim 19, whereinthe local decisions are selected from the group consisting of valveclosure upon gas detection, valve closure after receiving kill signalfrom other nodes.